Control of a three phase dual active bridge DC-DC converter using a metaheuristic algorithm based PI controller

Three-phase dual-active bridge (DC-DC) converters offer advantages such as bidirectional energy flow, high efficiency, a wide voltage range, and galvanic isolation, making them widely preferred in power electronics applications. However, maintaining the output voltage at the desired level requires an effective controller design to ensure stable performance under disturbance effects such as sudden voltage fluctuations and parameter variations. In this study, the basic operating principle and theoretical calculations of the converter are examined, and the design and control are optimized using a metaheuristic algorithm-based PI controller. The system performance under disturbance effects is evaluated in the MATLAB/Simulink (R2023b) environment, and the PI controller parameters are optimized using Particle Swarm Optimization (PSO), Artificial Bee Colony Algorithm (ABC), and Ant Colony Optimization (ACO) algorithms. The parameters optimized by PSO improve system performance by reducing rise time, settling time, and overshoot, leading to faster settling of the output voltage to the reference value. As a result, the study demonstrates the potential of a metaheuristic algorithm-optimized PI controller to enhance efficiency and provide a more stable system against disturbance effects in DC-DC converters.